ServiceNow Knowledge 2025: 4 major announcements to be aware of

AI transformation will affect 8 million roles in the U.S. alone according to ServiceNow Knowledge 2025. This revelation emphasizes how organizations must adapt to this fundamental change. The Venetian Resort in Las Vegas will hosted this landmark conference from May 6-8, 2025, where ServiceNow’s bold vision for work and enterprise technology took center stage. The timing proves crucial as AI solutions’ global effect could reach $22.3 trillion by 2030.

ServiceNow has revealed four groundbreaking announcements that matter to businesses in this ever-changing digital world. ServiceNow University leads the charge with plans to improve skills of 3 million learners by the end of 2027 to address the widening skills gap in an AI-driven world. The company’s new AI Control Tower gives organizations exceptional governance capabilities to direct and manage every AI agent from one central location. ServiceNow’s AI-powered CRM has become their fastest-growing workflow business with $1.4 billion in annual contract value and continues to improve customer experiences through intelligent automation. These breakthroughs support ServiceNow’s vision to create uninterrupted, AI-improved workflows that boost productivity while humans retain control. Gartner predicts that by 2028, enterprises using such AI governance platforms will achieve 30% higher customer trust ratings than their competitors.

Why ServiceNow is betting on AI to transform enterprise learning

AI technology’s rapid growth has created an urgent need to retrain the workforce. ServiceNow University emerged at ServiceNow Knowledge 2025 as a groundbreaking solution to this challenge. This state-of-the-art learning platform responds to changes in the global job market as AI reshapes workplace needs.

How ServiceNow University addresses the AI skills gap

ServiceNow University differs from typical corporate training programs through its personal touch to skill development. The platform uses advanced AI to give learners a custom toolkit that helps them switch careers or start tech positions. The detailed curriculum combines technical and human skills to help people secure their future careers.

“in the age of AI, we have an opportunity to unleash a human renaissance by helping our people reach their full potential, simplify their lives, and focus on the meaningful, innovative work that drives business success”.
– Jacqui Canney, Chief People and AI Enablement Officer at ServiceNow

This belief explains ServiceNow’s heavy investment in learning programs despite economic uncertainty.

The university’s design reflects a key insight: workplace changes need flexible learning that values how people learn on the job as much as the skills they gain. ServiceNow University encourages ongoing adaptation instead of quick fixes, putting people at the heart of learning.

Research from IDC shows this approach matters now more than ever. 90% of global enterprises face severe IT talent shortages that might cost them €6.20 trillion by 2025. The tech skills gap actually presents a talent growth chance—AI can help by automating technical tasks and making jobs available to people without computer science degrees.

What the Pearson research reveals about job disruption

ServiceNow and Pearson’s third annual report, coming this September, shows why these programs matter. The study predicts agentic AI will change millions of jobs across all fields. More than 8 million roles in the United States alone will transform due to agentic AI.

The research shows interesting regional differences in AI’s workforce effects:

• Germany expects 27% tech workforce growth by 2030
• The United States projects 36% tech workforce growth
• India leads with a projected 95% increase

The study revealed something unexpected: many highly affected roles aren’t in IT but in payroll, administration, and operations. This challenges what we thought we knew about AI’s impact on jobs.

Pearson Skills Outlook series shows white-collar roles face bigger changes than blue-collar jobs. About 30% of white-collar tasks could use Generative AI, while less than 1% of blue-collar tasks could do the same.

UK’s most affected white-collar jobs include:

• Medical Secretaries: 41% of tasks could be automated
• Communication Operators: 40% of tasks could be automated
• Book-Keepers, Payroll Managers and Wages Clerks: 39% of tasks could be automated

Blue-collar jobs like landscaping, mechanics, and construction need hands-on work or customer service that AI can’t easily copy. Jobs such as laundry workers, painters, and groundskeepers have almost 0% task automation potential.

Mike Howells, President of Pearson Workforce Skills, said: “As employees look to the future, understanding which jobs are at risk from AI allows them to prepare. They should also consider where new roles might be created by Gen AI”. His words show both the challenges and chances this change brings.

The study also shows which tasks AI can help with best. UK workers could save 19 million hours weekly by 2026 in areas like:

• Keeping up with expert knowledge (679,000 hours saved)
• Creating educational programs (665,000 hours saved)
• Making visual designs (525,000 hours saved)

Companies can let workers focus on human skills by automating simple tasks: strategic thinking, teamwork, caring for others, making decisions, solving problems, showing empathy, and leading teams.

How RiseUp supports underserved communities

ServiceNow helps more than its own workers through RiseUp with ServiceNow. This program gives underserved communities better access to tech, knowledge, and growth chances. It supports ServiceNow University’s goal to reach 3 million learners by 2027.

RiseUp creates new job paths for diverse communities while helping employers find and keep ServiceNow talent. ServiceNow believes that “We are passionate about inclusivity because inclusive teams encourage ideas and innovation”.

The program brings partners, customers, and universities together to solve talent issues differently. RiseUp finds hidden talent and gives them future skills instead of just filling current jobs. ServiceNow aims to train 1 million people globally on its platform, with Europe as a key focus.

This helps solve a big issue: 80% of UK jobs need digital skills, but talent shortages limit growth. The UK economy loses up to £63 billion yearly in potential GDP due to missing digital skills. Public sector faces bigger challenges with only 4% digital professionals compared to 8-12% in other industries.

RiseUp stands out because it’s flexible and easy to access. It offers funded NextGen programs like Skills Bootcamps in Service Design and Management, plus apprenticeships in Digital & Technology Solutions and Data Science. People learn ServiceNow skills along with broader digital training.

Employers benefit too. They can meet skilled NextGen graduates through networking events and speed-hiring days without paying for training or recruitment. The new Talent Connect makes this even better by listing job-ready people with both technical and people skills.

ServiceNow builds a new talent pipeline while supporting economic inclusion. Many participants come from underserved groups like refugees, women returning to work, and veterans. This diversity brings fresh ideas to the digital workforce and helps serve all users better.

How AI Control Tower brings visibility and trust to enterprise AI

“We are passionate about creating software that empowers technologists to drive business transformation. As you plot your journey through Knowledge, learn how ServiceNow enables IT leaders to leverage AI agent innovation to deliver value across the enterprise.”
– Pablo Stern, SVP & GM, Technology Workflows at ServiceNow

ServiceNow Knowledge 2025 revealed the AI Control Tower, a breakthrough solution that tackles a major challenge organizations face today – managing AI expansion across the enterprise. Organizations need centralized visibility, governance, and control as AI initiatives grow across departments and functions.

Why centralized AI governance is now essential

Enterprise AI adoption has created a complex ecosystem that needs reliable governance frameworks. Gartner research shows organizations using AI governance platforms will achieve 30% higher customer trust ratings and 25% better regulatory compliance scores than their competitors by 2028. These numbers show how unmanaged AI deployment brings substantial business risks.

AI governance establishes principles, policies, and responsible development practices that arrange AI tools and systems with ethical and human values. Organizations need frameworks and standards to guide AI research, development, and application. The lack of structure exposes them to several vulnerabilities:

• Inconsistent data quality and security standards
• Potential regulatory compliance failures
• Lack of transparency in AI decision-making
• Inability to track performance and effects
• Higher likelihood of ethical breaches and biased outcomes

Leaders have noticed these concerns. 60% of CEOs report they are learning about additional AI policies to alleviate risk. Risk Officers and Financial Officers (63%) focus on regulatory and compliance risks, yet only 29% believe these risks have proper solutions.

Multiple AI agents and models across business units make things more complex. Enterprises struggle with “Shadow AI” – unauthorized or unmonitored AI usage that can raise security and compliance risks dramatically without centralized oversight. Security teams cannot investigate AI-related incidents effectively due to this fragmentation.

Centralized governance helps organizations maximize their AI investments beyond risk reduction. Data leaders understand this, with over 65% making data governance their top priority in 2024. This change shows governance creates conditions for responsible breakthroughs and growth.

How Control Tower arranges AI with business strategy

ServiceNow’s AI Control Tower marks a major step forward in connecting AI initiatives to core business objectives. The platform provides critical business context to link AI projects with essential business services and technology through ServiceNow’s unified data architecture. Organizations can prioritize AI initiatives based on their business value potential.

The platform works as a detailed command center. It automates AI workflows while managing risk and measuring effects in real-time. Its dashboard offers operational insights that verify AI performance against key business outcomes like productivity and revenue impact. Organizations can monitor performance metrics, find areas to improve, and make data-driven investment decisions continuously.

AI Control Tower’s capabilities cover four vital areas:

1. Strategic Alignment – The platform matches AI initiatives with enterprise business and technology goals to deliver real value
2. Operational Efficiency – Simplified processes with automated workflows boost efficiency across the entire AI lifecycle
3. Performance Optimization – Continuous monitoring of AI metrics helps organizations allocate resources effectively
4. Risk Management – Real-time insights help maintain compliance and enforce AI governance best practices

Amit Zavery, President, Chief Product Officer, and Chief Operating Officer at ServiceNow, explains this fundamental change in managing AI: “As AI agents expand across enterprises, coordinating their work becomes as critical and complex as leading human employees, and companies need new tools to direct this new digital workforce”.

Most C-suite executives (80%) have a separate risk function for AI usage, but many organizations still use fragmented governance approaches. AI Control Tower solves this by centralizing strategy, governance, performance, and management across the AI ecosystem.

What makes it different from other AI management tools

ServiceNow’s AI Control Tower stands out through its all-encompassing approach to AI management and governance. The platform clarifies the complete data lifecycle while offering detailed transparency and governance capabilities, unlike solutions that address data visibility in isolation.

The platform offers unique features:

• Enterprise-wide AI visibility – Organizations can monitor and manage every AI agent, model, and workflow in one place—whether native to ServiceNow or from third parties
• End-to-end lifecycle management – AI Control Tower enables contextual decisions and enforces guardrails across the enterprise
• Integration with AI Agent Fabric – The platform works with ServiceNow’s AI Agent Fabric to enable native collaboration between agentic systems
• Unified platform approach – AI Control Tower runs on the ServiceNow AI Platform, bringing AI, data, and workflows together on a single, enterprise-grade foundation
• Full IT ecosystem mapping – Strategic decisions become easier with visibility into AI assets and their connection to business services

The platform lets customers see all AI agents in action, understand their tasks, govern and track their impact, alleviate risk, maintain security, and assign human managers to oversee their work. This oversight helps organizations handle transparency and explainability concerns.

Built-in governance, risk, and compliance (GRC) capabilities enable proactive risk management. This feature matters since 27% of public companies mention AI regulation as a risk in SEC filings.

Matt Murphy, partner at Menlo Ventures, notes: “We’re witnessing the convergence of privacy, AI governance, and data security. Traditional point solutions attempt to address data visibility in silos—fragmenting compliance, governance, and security at precisely the moment when AI adoption demands unified oversight”.

Dynamic dashboards provide operational insight and verify AI performance against key business outcomes. Organizations can optimize their AI investments continuously instead of making one-time deployment decisions.

Risk and security leaders get comprehensive tools to assess AI risks, monitor compliance, and maintain audit-ready governance. These features help organizations follow internal policies and external standards while reducing risk exposure.

ServiceNow emphasizes trust in AI Control Tower’s development. Abhi Sharma, CEO and co-founder of Relyance AI, states: “At the heart of AI’s progress lies a critical question: Are we building technologies that people can truly rely on? When transparency and explainability becomes a guiding principle, we lay the groundwork for responsible AI that enables, inspires, and meets the highest standards of transparency”.

How ServiceNow’s AI-powered CRM changes the customer experience

ServiceNow’s AI-powered CRM emerged as one of its most revolutionary offerings at the Knowledge 2025 conference. The solution changes how organizations interact with customers across digital channels. ServiceNow’s fastest-growing workflow business shows remarkable market momentum with $1.4 billion in annual contract value.

Why traditional CRMs fall short in the AI era

Traditional CRM systems can’t keep up with modern customer interactions. These legacy platforms work in isolation from other enterprise systems. This creates disconnected experiences that frustrate customers and employees alike. Customer service agents spend too much time switching between different applications. Nearly 70% of them report this issue, which reduces their effectiveness.

Legacy CRMs show clear limitations as customer expectations change. Modern consumers want personalized, contextual interactions at every touchpoint. Traditional systems can’t deliver this standard. Most legacy CRMs were built when customer interactions followed simple, linear paths. Now complex, omnichannel experiences define customer interactions.

Data fragmentation poses another challenge for traditional CRMs. Customer information sits in separate silos across marketing, sales, and service departments. This makes it impossible to build unified customer profiles. Service agents must search multiple systems manually. The result? Longer resolution times and inconsistent service quality.

Digital channels make these problems worse. Legacy systems need extensive custom coding to add new communication channels. This creates fragile architectures that cost too much to maintain and scale. Organizations end up managing complex point solutions that create more problems than they fix.

Traditional CRMs also lack smart features to predict customer needs or suggest next steps. They work mainly as record-keeping systems rather than engagement platforms. Their value stays limited to simple data storage and retrieval.

How AI agents automate and personalize customer experiences

ServiceNow’s AI-powered CRM reimagines customer relationship management. It adds intelligent agents directly into customer workflows. These AI agents work like digital colleagues. They understand, respond to, and fix customer issues quickly and accurately across channels.

The platform uses “case intelligence” to sort, prioritize, and route customer issues automatically. It looks at content, urgency, and complexity to send each inquiry to the right resource. This eliminates multiple transfers between departments.

AI agents in the system can:

• Analyze sentiment and intent from customer communications
• Give relevant suggestions to human agents in real-time
• Automate routine processes like appointment scheduling and order status updates
• Create personalized responses across email, chat, and messaging platforms
• Learn from interactions to improve future engagements

These features work in a unified workflow environment that connects customer service with other business functions. Service agents can trigger actions in other systems without switching screens. They can process returns, handle credits, or update subscriptions from one place.

Natural language processing helps the platform understand customer questions regardless of phrasing. It turns these requests into structured data for efficient processing. This smart language handling removes the strict, keyword-based limits of regular chatbots.

ServiceNow stands out by focusing on complete process automation instead of just conversation interfaces. Many vendors only automate customer conversations. ServiceNow automates the actual processes that fulfill customer requests. This difference leads to faster resolution times and better first-contact resolution rates.

The system excels at personalization through detailed customer profiles. These include interaction history, product ownership, service entitlements, and preferences. AI agents use these profiles to customize recommendations for each customer’s situation instead of generic answers.

What early adopters are reporting in terms of ROI

Organizations using ServiceNow’s AI-powered CRM see substantial returns. Early adopters report 25% to 40% faster case resolution times compared to previous systems.

These improvements create real cost savings. A global telecommunications provider saved $3.2 million yearly after deployment. A financial services firm cut its cost per contact by 31% while boosting customer satisfaction by 22 points.

Employee experience metrics show positive changes too. Agent turnover dropped by 18% on average among surveyed organizations. This improvement comes from removing repetitive tasks that cause burnout.

Customer metrics look equally good. First-contact resolution rates improved by 35% across industries. Customer effort scores went up by 28%. These changes link directly to higher Net Promoter Scores and customer retention.

Revenue benefits stand out clearly. Organizations see 7% higher cross-sell and upsell conversion rates. The platform spots and acts on sales opportunities during service interactions. Subscription businesses saw 12% higher renewal rates after implementation.

Implementation goes faster too. Organizations deploy the system 40% quicker than other CRM projects. About 65% need fewer customizations than expected. This quick setup contrasts sharply with the years-long cycles of legacy platforms.

Most telling, 83% of early adopters moved staff from routine tasks to valuable work. Teams now focus on solving complex problems, building relationships, and creating service innovations. This shift turns customer service from a cost center into a strategic advantage.

Total cost of ownership makes a compelling case. Organizations switching to ServiceNow’s unified platform spend 22% less on yearly licenses. They cut integration and maintenance costs by 35%. These savings add to the operational benefits.

A healthcare provider achieved 310% ROI in three years, breaking even in under six months. A manufacturing company calculated $4.7 million in five-year net present value. Benefits grew faster in years two and three as AI models improved.

Some industries show particularly strong outcomes. Financial services organizations improved regulatory compliance by 41% alongside other gains. Retail businesses increased conversion rates from service interactions by 28%. These results show how the platform adapts to different business needs and customer engagement styles.

How AI Agent Fabric enables a new era of intelligent collaboration

ServiceNow’s AI Agent Fabric stands out as a groundbreaking innovation among the key announcements at Knowledge 2025. This technology will transform how AI systems interact across the enterprise. The communication backbone works for entire AI ecosystems and enables smooth collaboration between intelligent systems that used to operate alone.

What makes agent-to-agent communication revolutionary

A transformation in how AI operates within organizations comes through AI Agent Fabric. The technology supports three vital communication patterns: AI agent-to-AI agent, AI agent-to-tool, and agentic system-to-agentic system interactions. Traditional AI solutions work independently, but this technology lets systems exchange information dynamically using standardized protocols.

The platform uses common communication standards including Model Context Protocol (MCP) and Agent2Agent protocol (A2A). These protocols allow ServiceNow’s AI agents to share context, coordinate actions, and achieve outcomes in real time with third-party systems. This solution addresses a key challenge in enterprise AI deployment – intelligent systems couldn’t cooperate effectively across organizational boundaries.

Organizations struggled with isolated AI implementations that couldn’t share information or context before this innovation. AI Agent Fabric turns these disconnected tools into coordinated teams of digital workers that work as one intelligent system. Research shows AI agents provide the most value when deployed together to improve efficiency and boost decision-making across the enterprise.

How ServiceNow is building an open ecosystem with partners

ServiceNow designed AI Agent Fabric as an open platform that works with multiple communication protocols. Zilbershot from ServiceNow noted, “it’s less about the protocol and more about the capability… we really look at ourselves as an open platform, and we will be able to support all the common protocols that are available out there”.

The open ecosystem approach has attracted major integration partners:

• Technology leaders: Microsoft, Google Cloud, IBM, Cisco, Adobe
• Specialized providers: Accenture, Box, Jit, Moonhub, RADCOM, UKG, Zoom

Organizations can create smooth, end-to-end workflows between different agents thanks to these partnerships. The integration with Google’s A2A protocol, to name just one example, allows AI agents to communicate securely, exchange information, and coordinate actions in enterprise platforms and applications of all types.

Major technology partnerships show a strategic response to what enterprises just need – unified automation. Organizations in Brazil have started adopting AI solutions, using ServiceNow’s features and integrations with systems like Microsoft Copilot to streamline operations and control costs.

What this means for the future of enterprise automation

ServiceNow’s vision of bringing AI, data, and workflows together in one ecosystem becomes complete with AI Agent Fabric and the recently announced Workflow Data Fabric. Experts see this integration as the next step in enterprise automation—agentic process automation (APA).

Organizations can move beyond task-level automation with APA. Instead of the typical 20-30% of processes, they can automate 50% or more operations autonomously. This represents a fundamental change in enterprise automation approaches. AI systems can handle end-to-end workflows across departments while responding to data and making decisions in real time.

Human-AI and AI-AI interactions will become more common in future workplaces. Networks of AI agents will work as intelligent teams that cooperate, learn, and operate autonomously to improve business efficiency. Organizations will have networks of intelligent AI agents that find each other, cooperate, and complete tasks efficiently across platforms.

ServiceNow’s partnership with NVIDIA enables a new class of intelligent AI agents across the enterprise. The recently launched Apriel Nemotron 15B reasoning model delivers advanced reasoning capabilities for powering agentic AI workflows at scale.

ServiceNow now stands at the vanguard of what experts call a fundamental change in enterprise automation. The company leads the transformation from isolated AI implementations to connected, intelligent systems that work together to solve complex business challenges.

Conclusion

ServiceNow Knowledge 2025 shows how AI, data, and workflows naturally come together to shape enterprise technology’s future. The four major announcements in this piece – ServiceNow University, AI Control Tower, AI-powered CRM, and AI Agent Fabric – tackle the biggest challenges companies face as they adopt AI.

ServiceNow University tackles the skills gap that AI disruption has created. White-collar jobs could see up to 40% of their tasks automated. AI Control Tower gives you a framework to manage AI agents responsibly. You can address transparency, risk management, and strategic goals effectively. Research shows companies using these platforms will see 30% higher customer trust ratings by 2028.

The company’s AI-powered CRM has already generated $1.4 billion in annual contract value. It shows how smart automation creates tailored customer experiences and cuts resolution times dramatically. Companies that adopted early report 25-40% better case resolution efficiency. They also saw major cost savings and happier employees. These results explain why it has become ServiceNow’s fastest-growing workflow business.

AI Agent Fabric rounds out this ecosystem. It lets AI systems work together as coordinated teams instead of separate tools. This advanced technology lays the groundwork for process automation that could run 50% of operations on its own. Traditional automation methods only reach 20-30%.

These innovations go beyond simple product improvements. They show ServiceNow’s detailed vision of an AI-enhanced future. Human and digital workers can cooperate naturally while humans keep control. Companies that take this integrated approach will likely pull ahead as AI continues to alter the enterprise map through 2025 and beyond.

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